La notion de contexte est fondamentale dans le champ de l’informatique ubiquitaire. En particulier lorsque des services assistent un utilisateur dans ses activités quotidiennes. Parce qu’elle implique plusieurs disciplines, une maison équipée d’informatique ubiquitaire dédiée au maintien à domicile de personnes âgées demande l’implication d’une variété d’intervenants, tant pour concevoir et développer des services d’assistance, que pour déployer et maintenir l’infrastructure sous-jacente. Cette grande diversité d’intervenants correspond à une diversité de contextes. Ces différents contextes sont généralement étudiés séparément, empêchant toute synergie. Cette thèse présente une méthodologie permettant d’unifier la conception et le développement de services sensibles au contexte et de répondre aux besoins de tout type d’intervenant. Dans un premier temps, nous traitons les besoins des intervenants concernant l’infrastructure de capteurs/actionneurs : installation, maintenance et exploitation. Le modèle d’infrastructure de capteurs et un ensemble de règles en résultant permettent de superviser en continu l’infrastructure et de détecter des dysfonctionnements. Cette supervision simplifie le processus de développement d’applications, en faisant abstraction des problèmes d’infrastructure. Dans un second temps, nous analysons un large éventail de services d’assistance domiciliaire dédié aux personnes âgées, en considérant la variété des besoins des intervenants. Grâce à cette analyse, nous généralisons l’approche de modèle d’infrastructure à tout type de services. Notre méthodologie permet de définir des services de façon unifiée, à travers un langage dédié, appelé Maloya, exprimant des règles manipulant les concepts d’état et d’évènement. Nous avons développé un compilateur de notre langage vers un langage événementiel dont l’exécution s’appuie sur un moteur de traitement d’évènements complexes (CEP). Nous avons validé notre approche en définissant un large éventail de services d’assistance à la personne, à partir de services existants, et concernant l’ensemble des intervenants du domaine. Nous avons compilé et exécuté les services Maloya sur un moteur de traitement d’évènements complexes. Les performances obtenues en terme de latence et d’occupation mémoire sont satisfaisantes pour le domaine et compatible avec une exécution 24 heures sur 24 sur le long terme. / The notion of context is fundamental to the field of pervasive computing, and in particular when such services are dedicated to assist a user in his daily activities. Being at the crossroad of various fields, a context-aware home dedicated to aging in place involves a variety of stakeholders to design and develop assistive services, as well as to deploy and maintain the underlying infrastructure. This considerable diversity of stakeholders raises correspondingly diverse context dimensions : each service relies on specific contexts (e.g., sensor status for a maintenance service, fridge usage for a meal activity recognition service). Typically, these contexts are considered separately, preventing any synergy. This dissertation presents a methodology for unifying the design and development of various domestic context-aware services, which addresses the requirements of all the stakeholders. In a first step, we handle the needs of stakeholders concerned by the sensors infrastructure : installers, maintainers and operators. We define an infrastructure model of a home and a set of rules to continuously monitor the sensor infrastructure and raise failure when appropriate. This continuous monitoring simplifies application development by abstracting it from infrastructure concerns. In a second step, we analyze a range of services for aging in place, considering the whole diversity of stakeholders. Based on this analysis, we generalize the approach developed for the infrastructure to all assistive services. Our methodology allows to define unified services, in the form of rules processing events and states. To express such rules, we define a domain-specific design language, named Maloya. We developed a compiler from our langage using as a backend an event processing language, which is executed on a complex event processing (CEP) engine. To validate our approach, we define a wide range of assistive services with our language, which reimplement existing deployed services belonging to all of the stakeholders. These Maloya services were deployed and successfully tested for their effectiveness in performing the specific tasks of the stakeholders. Latency and memory consumption performance turned out to be fully compatible with a 24/7 execution in the long run.

La détection d’évènements complexes dans les flux d’évènements est un domaine qui a récemment fait surface dans le ecommerce. Notre partenaire industriel Cdiscount, parmi les sites ecommerce les plus importants en France, vise à identifier en temps réel des scénarios de navigation afin d’analyser le comportement des clients. Les objectifs principaux sont la performance et la mise à l’échelle : les scénarios de navigation doivent être détectés en moins de quelques secondes, alorsque des millions de clients visitent le site chaque jour, générant ainsi un flux d’évènements massif.Dans cette thèse, nous présentons Auros, un système permettant l’identification efficace et à grande échelle de scénarios de navigation conçu pour le eCommerce. Ce système s’appuie sur un langage dédié pour l’expression des scénarios à identifier. Les règles de détection définies sont ensuite compilées en automates déterministes, qui sont exécutés au sein d’une plateforme Big Data adaptée au traitement de flux. Notre évaluation montre qu’Auros répond aux exigences formulées par Cdiscount, en étant capable de traiter plus de 10,000 évènements par seconde, avec une latence de détection inférieure à une seconde. / Pattern detection over streams of events is gaining more and more attention, especially in the field of eCommerce. Our industrial partner Cdiscount, which is one of the largest eCommerce companies in France, aims to use pattern detection for real-time customer behavior analysis. The main challenges to consider are efficiency and scalability, as the detection of customer behaviors must be achieved within a few seconds, while millions of unique customers visit the website every day,thus producing a large event stream. In this thesis, we present Auros, a system for large-scale an defficient pattern detection for eCommerce. It relies on a domain-specific language to define behavior patterns. Patterns are then compiled into deterministic finite automata, which are run on a BigData streaming platform. Our evaluation shows that our approach is efficient and scalable, and fits the requirements of Cdiscount.

On assiste ces dernières années à une explosion des usages dans l’Internet des objets. La démocratisation de ce monde de capteurs est le fruit, d’une part de la baisse drastique des coûts dans l’informatique embarquée, d’autre part d’un support logiciel toujours plus mature. Que ce soit au niveau des protocoles et des réseaux (CoAP, IPv6, etc) ou de la standardisation des supports de développement, notamment sur microprocesseurs ATMEL, les outils à disposition permettent chaque jour une plus grande homogénéisation dans la communication entre des capteurs toujours plus variés. Cette diversification rassemble chaque jour des utilisateurs aux attentes et aux domaines de compétence différents, avec chacun leur propre compréhension des objets connectés. La complexification des réseaux de capteurs, confrontée à cette nécessité d’adresser des usages fondamentalement différents, pose problème. Sur la base d’un même réseau de capteurs hétéroclite, il est crucial de pouvoir répondre aux besoins de chacun des utilisateurs, sans réclamer d’eux une maîtrise du réseau de capteurs dépassant exagérément leur domaine de compétence. L’outil décrit dans ce document se propose d’adresser cette problématique au travers d’un moteur de requête dédié au traitement des données issus des capteurs. Pour ce faire, il repose sur une modélisation des capteurs au sein de différents contextes, chacun à même de répondre à un besoin utilisateur précis. Sur la base de ce modèle est mis à disposition un langage dédié pour le traitement des événements complexes issus des données mesurées par les capteurs. L’implémentation de cet outil permet en outre d’interagir avec d’éventuelles fonctionnalités d’actuation du réseau de capteurs. / Usages of the internet of things experience an exponential growth these last few years. As a matter of fact, this is the result of, on one hand the significantly lowercosts in embedded computing systems, on the other hand the maturing of the software layers. From protocols and networks (CoAP, IPv6, etc) to standardization of ATMEL microcontrollers, tools at hand allow a better communication between more and more various sensors. This diversification gather every day users with different needs, expectations and fields of expertise, each one of them having his own approch, his own understanding of the connected things. The main issue concerns the complexity of the sensor networks, with regard to this necessity to address deeply different usages. Based on a single heterogeneous sensor network, it is critical to be able to meet the needs of each user, without having them to master the network beyond their own field of expertise. The tool described in this document aims at addressing this issue via a query engine dedicated to the processing of data collected from the sensors. Towards this end, it relies on a modelling of the sensors within several contexts, each of them reflecting a specific usage. On this basis a domain-specific language is provided, allowing complex event processing over the data monitored by the sensors. Furthermore, the implementation of this tool allows to interact with optional actuation functionalities of the sensor network.

Long wait times are a global issue in the healthcare sector, particularly in Canada. Despite numerous research findings on wait time management, the issue persists. This is partly because for a given hospital, the data required to conduct wait times analysis is currently scattered across various information systems. Moreover, such data is usually not accurate (because of possible human errors), imprecise and late. The whole situation contributes to the current state of wait times. This thesis proposes a location-aware business process management system for real-time care process monitoring. More precisely, the system enables an improved visibility of process execution by gathering, as processes execute, accurate and granular process information including wait time measurements. The major contributions of this thesis include an architecture for the system, a prototype taking advantages of commercial real-time location system combined with a business process management system to accurately measure wait times, as well as a case study based on a real cardiology process from an Ontario hospital.

Concevoir les produits complexes tels que les avions, les hélicoptères, et les lanceurs requière l'utilisation de processus standardisés ayant des fondements robustes. Ces processus doivent être exécutés dans le contexte d'environnements collaboratifs interorganisationnels souvent dynamiques. Dans ce manuscrit, nous présentons un cadre formel qui assure une interopérabilité continue dans le temps pour les processus inter-organisationnels dans les environnements dynamiques. Nous proposons un langage de modélisation déclaratif pour définir des contrats qui capturent les objectifs de chaque partenaire intervenant dans la collaboration. Les modèles de contrats construits avec ce langage sous-spécifient les objectifs de la collaboration en limitant les détails capturés durant la phase de construction du contrat. Cette sous-spécification réduit le couplage entre les partenaires de la collaboration. Néanmoins, moins de couplage implique l'apparition de certaines inadéquations quand les processus des partenaires vont s'échanger des messages lors de la phase d'exécution. Par conséquent, nous développons un algorithme de médiation automatique qui est bien adapté pour les environnements dynamiques. Nous conduisons des évaluations de performance sur cet algorithme qui vont démontrer son efficience par rapport aux approches de médiation existantes. Ensuite, nous étendons notre cadre avec un ensemble d'opérations d'administration qui permettent la réalisation de modifications sur l'environnement collaboratif. Nous développons un algorithme qui évalue l'impact des modifications sur les partenaires. Cet algorithme va ensuite décider si la modification doit être réalisée à l'instant ou bien retardée en attendant que des conditions appropriées sur la configuration de l'environnement dynamique soient satisfaites. Pour savoir comment atteindre ces conditions, nous utilisons l'algorithme de planning à base de graphe. Cet algorithme détermine l'ensemble des opérations qui doivent être exécutées pour atteindre ces conditions / Designing complex products such as aircrafts, helicopters and launchers must rely on well-founded and standardized processes. These processes should be executed in the context of dynamic cross-organizational collaboration environments. In this dissertation, we present a formal framework that ensures sustainable interoperability for cross-organizational processes in dynamic environments. We propose a declarative modeling language to define contracts that capture the objectives of each partner in the collaboration. Contract models built using this language under-specify the objectives of the collaboration by limiting the details captured at design-time. This under-specification decreases the coupling between partners in the collaboration. Nevertheless, less coupling leads to the creation of mismatches when partners’ processes will exchange messages at run-time. Accordingly, we develop an automatic mediation algorithm that is well adapted for dynamic environments. We conduct a thorough evaluation of this algorithm in the context of dynamic environments and compare it with existing mediation approaches which will prove its efficiency. We then extend our framework with a set of management operations that help realize the modifications on the collaboration environment at run-time. We develop an algorithm that assesses the impact of modifications on the partners in the collaboration environment. Then, this algorithm decides if the modification can be realized or should be postponed to wait for appropriate conditions. In order to figure out how to reach these appropriate conditions, we use the planning graph algorithm. This algorithm determines the raw set of management operations that should be executed in order to realize these conditions. A raw set of management operations cannot be executed by an engine unless its operations are encapsulated in the right workflow patterns. Accordingly, we extend this planning algorithm in order to generate an executable workflow from the raw set of operations. We evaluate our extension against existing approaches regarding the number and the nature of workflow patterns considered when generating the executable workflow. Finally, we believe that monitoring contributes in decreasing the coupling between partners in a collaboration environment

Durant la dernière décennie, les architectures orientées services (SOA) d'une part et la gestion des processus business (BPM) d'autre part ont beaucoup évolué et semblent maintenant en train de converger vers un but commun qui est de permettre à des organisations complètement hétérogènes de partager de manière flexible leurs ressources dans le but d'atteindre des objectifs communs, et ce, à travers des schémas de collaboration avancée. Ces derniers permettent de spécifier l'interconnexion des processus métier de différentes organisations. La nature dynamique et la complexité de ces processus posent des défis majeurs quant à leur bonne exécution. Certes, les langages de description de chorégraphie aident à réduire cette complexité en fournissant des moyens pour décrire des systèmes complexes à un niveau abstrait. Toutefois, rien ne garantit que des situations erronées ne se produisent pas suite, par exemple, à des interactions "mal" spécifiées ou encore des comportements malhonnêtes d'un des partenaires. Dans ce manuscrit, nous proposons une approche décentralisée qui permet la supervision de chorégraphies au moment de leur exécution et la détection instantanée de violations de séquences d'interaction. Nous définissons un modèle de propagation hiérarchique pour l'échange de notifications externes entre les partenaires. Notre approche permet une génération optimisée de requêtes de supervision dans un environnement événementiel, et ce, d'une façon automatique et à partir de tout modèle de chorégraphie / Cross-organizational service-based processes are increasingly adopted by different companies when they can not achieve goals on their own. The dynamic nature of these processes poses various challenges to their successful execution. In order to guarantee that all involved partners are informed about errors that may happen in the collaboration, it is necessary to monitor the execution process by continuously observing and checking message exchanges during runtime. This allows a global process tracking and evaluation of process metrics. Complex event processing can address this concern by analyzing and evaluating message exchange events, to the aim of checking if the actual behavior of the interacting entities effectively adheres to the modeled business constraints. In this thesis, we present an approach for decentralized monitoring of cross-organizational choreographies. We define a hierarchical propagation model for exchanging external notifications between the collaborating parties. We also propose a runtime event-based approach to deal with the problem of monitoring conformance of interaction sequences. Our approach allows for an automatic and optimized generation of rules. After parsing the choreography graph into a hierarchy of canonical blocks, tagging each event by its block ascendancy, an optimized set of monitoring queries is generated. We evaluate the concepts based on a scenario showing how much the number of queries can be significantly reduced

With the introduction of Wireless Multimedia Sensor Networks, large-scale remote outdoor surveillance applications where the majority of the cameras will be battery-operated are envisioned. These are the applications where the frequency of incidents is too low to employ permanent staffing such as monitoring of land and marine border, critical infrastructures, bridges, water supplies, etc. Given the inexpensive costs of wireless resource constrained camera sensors, the size of these networks will be significantly larger than the traditional multi-camera systems. While large number of cameras may increase the coverage of the network, such a large size along with resource constraints poses new challenges, e.g., localization, classification, tracking or reactive behavior. This dissertation proposes a framework that transforms current multi-camera networks into low-cost and reactive systems which can be used in large-scale remote surveillance applications. Specifically, a remote surveillance system framework with three components is proposed: 1) Localization and tracking of objects / 2) Classification and identification of objects / and 3) Reactive behavior at the base-station. For each component, novel lightweight, storage-efficient and real-time algorithms both at the computation and communication level are designed, implemented and tested under a variety of conditions. The results have indicated the feasibility of this framework working with limited energy but having high object localization/classification accuracies. The results of this research will facilitate the design and development of very large-scale remote border surveillance systems and improve the systems effectiveness in dealing with the intrusions with reduced human involvement and labor costs.

La réduction de la taille des équipements et l’avènement des communications sans fil ont fortement contribué à l’avènement d’une informatique durable. La plupart des applications informatiques sont aujourd’hui construites en tenant compte de cet environnement ambiant dynamique. Leur développement et exécution nécessite des infrastructures logicielles autorisant des entités à s’exécuter, à interagir à travers divers modes (synchrone et asynchrone), à s’adapter à leur(s) environnement(s) notamment en termes : - de consommation de ressources (calcul, mémoire, support de stockage, bases de données, connexions réseaux, ...), - de multiplicité des sources de données (illustrée par le Web, les capteurs, compteurs intelligents, satellites, les bases de données existantes, ...) - des formats multiples des objets statiques ou en flux (images, son, vidéos). Notons que dans beaucoup de cas, les objets des flux doivent être homogénéisées, enrichies, croisées, filtrées et agrégées pour constituer in fine des produits informationnels riches en sémantique et stratégiques pour les applications ou utilisateurs. Les systèmes à base d'événements particulièrement bien adaptés à la programmation de ce type d’applications. Ils peuvent offrir des communications anonymes et asynchrones (émetteurs/serveurs et récepteurs /clients ne se connaissent pas) qui facilitent l'interopération et la collaboration entre des services autonomes et hétérogènes. Les systèmes d’événements doivent être capables d'observer, transporter, filtrer, agréger, corréler et analyser de nombreux flux d’événements produits de manière distribuée. Ces services d’observation doivent pouvoir être déployés sur des architectures distribuées telles que les réseaux de capteurs, les smart-grid, et le cloud pour contribuer à l’observation des systèmes complexes et à leur contrôle autonome grâce à des processus réactifs de prise de décision. L’objectif de la thèse est de proposer un modèle de composition distribuée de flux d’événements et de spécifier un service d’événements capable de réaliser efficacement l’agrégation, la corrélation temporelle et causale, et l’analyse de flux d’événements dans des plateformes distribuées à base de services. TRAVAIL A REALISER (i) Etat de l’art - Systèmes de gestion de flux événements - Services et infrastructures d’événements distribués - Modèles d’événements (ii) Définition d’un scénario d’expérimentation et de comparaison des approches existantes. (iii) Définition d’un modèle de composition distribuée de flux d’événements à base de suscriptions (iv) Spécification et implantation d’un service distribuée de composition de flux d’événements. / The reduction in the size of equipments and the advent of wireless communications have greatly contributed to the advent of sustainable IT . Most computer applications today are built taking into account the dynamic ambient environment. Their development and execution need software infrastructure allowing entities to execute , interact through a variety of modes (synchronous and asynchronous ) , has to adapt to their (s) environment (s ), particularly in terms of: - resource consumption ( computation , memory , storage media , databases , networks connections , ... ) - the multiplicity of data sources ( illustrated by the Web , sensors, smart meters, satellites, existing data bases .. . ) - multiple formats of static objects or streams (images , sounds, videos ) . Note that in many cases , stream's objects have to be homogenized, enriched, filtered and aggregated to form informations rich in semantic and strategic for applications or end users. Event based systems are particularly well suited to the programming of such applications. They can offer anonymous and asynchronous communications ( transmitters / receivers and servers / clients do not know each others) that facilitate interoperation and cooperation between autonomous and heterogeneous services. The event systems should be able to observe, transport, filter, aggregate, correlate and analyze many events streams produced in a distributed way. These observation services must be able to be deployed on distributed architectures , such as sensor networks , smart -grid and cloud, to contribute to the observation of complex systems and their self-control via reactive decisions making processes. The aim of the thesis is to propose a model for distributed event flows composition and specify an event service that can effectively realize the aggregation , temporal and causal correlation , and analysis of flow events in distributed service -based platforms. WORK TO BE PERFORMED (i) State of the art: - Events flow management systems - distributed event services - event model ( ii ) Definition of a scenario for experimentation and comparison of existing approaches. ( iii ) Definition of a model of composition delivered a stream of events based superscriptions ( iv ) Specification and implementation of a distributed event flow composition service

abstract: Clinical Decision Support (CDS) is primarily associated with alerts, reminders, order entry, rule-based invocation, diagnostic aids, and on-demand information retrieval. While valuable, these foci have been in production use for decades, and do not provide a broader, interoperable means of plugging structured clinical knowledge into live electronic health record (EHR) ecosystems for purposes of orchestrating the user experiences of patients and clinicians. To date, the gap between knowledge representation and user-facing EHR integration has been considered an “implementation concern” requiring unscalable manual human efforts and governance coordination. Drafting a questionnaire engineered to meet the specifications of the HL7 CDS Knowledge Artifact specification, for example, carries no reasonable expectation that it may be imported and deployed into a live system without significant burdens. Dramatic reduction of the time and effort gap in the research and application cycle could be revolutionary. Doing so, however, requires both a floor-to-ceiling precoordination of functional boundaries in the knowledge management lifecycle, as well as formalization of the human processes by which this occurs. This research introduces ARTAKA: Architecture for Real-Time Application of Knowledge Artifacts, as a concrete floor-to-ceiling technological blueprint for both provider heath IT (HIT) and vendor organizations to incrementally introduce value into existing systems dynamically. This is made possible by service-ization of curated knowledge artifacts, then injected into a highly scalable backend infrastructure by automated orchestration through public marketplaces. Supplementary examples of client app integration are also provided. Compilation of knowledge into platform-specific form has been left flexible, in so far as implementations comply with ARTAKA’s Context Event Service (CES) communication and Health Services Platform (HSP) Marketplace service packaging standards. Towards the goal of interoperable human processes, ARTAKA’s treatment of knowledge artifacts as a specialized form of software allows knowledge engineers to operate as a type of software engineering practice. Thus, nearly a century of software development processes, tools, policies, and lessons offer immediate benefit: in some cases, with remarkable parity. Analyses of experimentation is provided with guidelines in how choice aspects of software development life cycles (SDLCs) apply to knowledge artifact development in an ARTAKA environment. Portions of this culminating document have been further initiated with Standards Developing Organizations (SDOs) intended to ultimately produce normative standards, as have active relationships with other bodies. / Dissertation/Thesis / Doctoral Dissertation Biomedical Informatics 2018

[pt] O crescimento da Internet das Coisas (IoT) nos trouxe a oportunidade de criar aplicações em diversas áreas com o uso de sensores e atuadores. Um dos problemas encontrados em sistemas de IoT é a dificuldade de adicionar relações semânticas aos dados brutos produzidos por estes sensores e conseguir inferir novos fatos a partir destas relações. Além disso, devido à natureza destes sistemas, os dados produzidos por eles, conhecidos como streams, precisam ser analisados em tempo real. Streams são uma sequência de elementos de dados com variação de tempo e que não devem ser tratados como dados a serem armazenados para sempre e consultados sob demanda. Os dados em streaming precisam ser consumidos rapidamente por meio de consultas contínuas que analisam e produzem novos dados relevantes. A capacidade de inferir novas relações semânticas sobre dados em streaming é chamada de inferência sobre streams. Nesta pesquisa, propomos um modo semântico e um mecanismo para processamento e inferência sobre streams em tempo real baseados em Processamento de Eventos Complexos (CEP), RDF (Resource Description Framework) e OWL (Web Ontology Language). Apresentamos um middleware que suporta uma inferência contínua sobre dados produzidores por sensores. As principais vantagens de nossa abodagem são: (a) considerar o tempo como uma relação-chave entre a informação; (b) processamento de fluxo por ser implementado usando o CEP; (c) é geral o suficiente para ser aplicado a qualquer sistema de gerenciamento de fluxo de dados (DSMS). Foi desenvolvido no Laboratório de Colaboração Avançada (LAC) utlizando e um estudo de caso no domínio da detecção de incêndio é conduzido e implementado, elucidando o uso de inferência em tempo real sobre streams. / [en] The growth of the Internet of Things (IoT) has brought the opportunity to create applications in several areas, with the use of sensors and actuators. One of the problems encountered in IoT systems is the difficulty of adding semantic relations to the raw data produced by the sensors and being able to infer new facts from these relations. Moreover, due to the fact that many IoT applications are online and need to react instantly on sensor data collected by them, they need to be analyzed in real-time. Streams are a sequence of time-varying data elements that should not be stored forever and queried on demand. Streaming data needs to be consumed quickly through ongoing queries that continue to analyze and produce new relevant data, i.e. stream of output/result events. The ability to infer new semantic relationships over streaming data is called Stream Reasoning. We propose a semantic model and a mechanism for real-time data stream processing and reasoning based on Complex Event Processing (CEP), RDF (resource description structure) and OWL (Web Ontology Language). This work presents a middleware service that supports continuous reasoning on data produced by sensors. The main advantages of our approach are: (a) to consider time as a key relationship between information; (b) flow processing can be implemented using CEP; (c) is general enough to be applied to any data flow management system (DSMS). It was developed in the Advanced Collaboration Laboratory (LAC) and a case study in the field of fire detection is conducted and implemented, elucidating the use of real-time inference on streams.